Key Takeaways
- Talent intelligence helps you turn your raw assessment data into a strategic asset, using which you can make informed decisions about hiring and workforce planning.
- To build a structured skills mapping workflow (for a role), define the competencies you need, align assessments to them, standardize data, and translate scores into a proficiency framework.
- Use metrics from situational judgment tests, cognitive ability assessments, and role-specific simulations to predict on-the-job performance.
- If you transform your numerical scores into descriptive competency levels, it can make your data understandable and actionable for managers.
- Visualizing data through a skills matrix or heat map provides an immediate, at-a-glance overview of organizational capabilities and highlights critical talent gaps.
Organizations are sitting on a goldmine of data, yet many fail to tap into its full potential. Every assessment, test, and evaluation you take contains valuable insights into a candidate’s or employee’s capabilities. And this data can actually guide your hiring, development, and workforce planning with unparalleled precision.
The process of converting raw assessment results into actionable business insights involves skills mapping. But how do you design a workflow that extracts deep talent intelligence from your test data, enabling you to build a more agile, skilled, and future-ready workforce? Or, how do you connect assessment metrics to on-the-job performance, translate scores into meaningful competency levels, and use technology to automate and visualize your organization’s skills landscape? Let’s find out.
Designing a Skills Mapping Workflow from Assessment Data
An effective skills mapping workflow creates a systematic bridge between assessment results and your talent capabilities. This process turns abstract data points into a strategic map of employee skills. Here’s the step-by-step process to do it.
Step 1: Define Your Core Competencies
Start by identifying the critical competencies required for success in various roles and across the organization. This involves collaborating with department heads and team leaders to define both technical (hard) skills and behavioral (soft) skills. For instance, a software developer role might require proficiency in Python (hard skill) as well as strong problem-solving and collaboration abilities (soft skills).
Step 2: Align Assessments with Competencies
Once you’ve defined your competencies, make sure to design your assessments in a way that they can measure them accurately. To achieve this, you’ll need to customize your assessments so you can directly evaluate the specific skills you’ve identified in the first step.
What you need is a combination of psychometric tests for behavioral traits, situational judgment tests for decision-making, and technical skill tests for functional expertise to get a holistic view of each candidate.
Step 3: Standardize Data Collection and Scoring
Establish a standardized method for administering tests and scoring results. This ensures that the data you collect is reliable and comparable across all candidates and employees. The goal here is to create a unified data set that you can analyze systematically, removing biases and inconsistencies that can arise from varied testing environments or evaluation criteria.
Step 4: Map Scores to a Competency Framework
Finally, develop a framework that translates raw test scores into defined competency levels. (They can be Novice, Intermediate, Proficient, Expert).
Let’s say, you set a score between 70-80% on a project management to simulate an “Intermediate” proficiency level. It can help you immediately understand the data even if you’re a non-technical stakeholder or hiring manager.
Which Assessment Metrics Best Predict On-the-Job Performance?
Not all assessment metrics are created equal. To gain true talent intelligence, you need to focus on the data points that have a proven correlation with success in a role. For instance:
- Situational Judgment Test (SJT) Performance: A predictor of problem-solving skills and decision-making quality of candidates.
- Cognitive Ability Scores: It measures the logical reasoning, numerical reasoning, and critical thinking of your applicants required for the job role performance.
- Behavioral Assessment Data: These assessments uncover a candidate’s inherent work style, personality traits, and motivations.
- Role-Specific Skill Simulations: For technical roles, you need to predict performance better than a hands-on simulation. So, here, you need metrics from coding tests, design challenges, or financial modeling exercises to understand the candidate’s ability to perform the core functions of the job.
Tools for Automating Skill Extraction from Assessment Results
Manually analyzing thousands of assessment data points is impractical and prone to error. Fortunately, you can automate the extraction of skills and build a talent intelligence platform. Here’s how to go about it:
- Use modern assessment platforms. They often come with built-in analytics modules that automatically map results to predefined competency frameworks. These platforms can help you process data from various test types – cognitive, behavioral, and technical – and generate comprehensive candidate profiles that highlight skill strengths and weaknesses.
- For assessments that involve written or verbal responses, such as video interviews or open-ended questions, you need AI and NLP tools. They help you analyze responses for keywords, sentiment, and communication style, automatically extracting evidence of skills like “strategic thinking” or “persuasive communication.”
- You can also connect tools like Tableau, Power BI, and specialized HR analytics platforms to your assessment data sources. They allow you to create automated dashboards and reports, turning complex data sets into easily digestible charts and graphs.
Frequently Asked Questions (FAQ)
Q1: What is talent intelligence?
A1: Talent intelligence is the process of collecting, analyzing, and applying data about the labor market, competitors, and your own workforce to make strategic talent decisions.
Q2: How is skills mapping different from a simple skills inventory?
A2: A skills inventory is a simple list of skills an employee claims to have. Skills mapping validates those skills through objective assessments and maps them to predefined proficiency levels.
Q3: Can we use our existing assessment tools for skills mapping?
A3: Yes, you can, if your assessment tools measure specific competencies and produce reliable data.
Q4: How do we get started with skills mapping if we have no process in place?
A4: Simple. Start small. Choose one critical role or department to pilot your skills mapping initiative. Define the top 5-7 essential skills for that role, select or design assessments to measure them, and create a simple competency framework.
